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spatial omics datasets. The position will also contribute to multi-modal data integration efforts that combine imaging, genomics, and machine learning approaches. Key Responsibilities Data Processing
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rapid and significant shifts in power consumption, next-generation high-performance computing (HPC) platforms used in machine learning, big data and artificial intelligence (AI) based applications (CPUs
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control subjects based on diffusion MRI images and functional MRI responses. Duties include: Developing machine-learning and/or deep learning pipelines for classifying patients of optic neuropathies and
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) platforms used in machine learning, big data and artificial intelligence (AI) based applications (CPUs, GPUs, AI accelerators etc.) require high power demands with optimized power distribution networks (PDNs
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(HPC) platforms used in machine learning, big data and artificial intelligence (AI) based applications (CPUs, GPUs, AI accelerators etc.) require high power demands with optimized power distribution
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of transmission electron microscopes and/or scanning electron microscopes Knowledge of artificial intelligence and machine learning and their applications in electron microscopy Knowledge of computer programming
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student to start in September 2025 (preferably) or January 2026 to study aspects of sensory physiology and learning in the context of pollination ecology. Using honey bees and other arthropods, our
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. It was Mrs. Killam's desire that those selected to receive scholarships: "Be likely to contribute to the advancement of learning or to win distinction in a profession. A Killam scholar should not be a
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centrifugal, digital, capillary, pressure, or microvalve-based microfluidics. Experience in deep-learning and artificial intelligence in the field of microfluidics to support applications such as high
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to shine! Work where the world comes to create, discover and learn. We are consistently one of Canada’s top-ranked universities and leading research institutions. With more than 8,900 students, two